Generalized Linear Models Discriminant Analysis Kernel ridge regression SVMs Stochastic Gradient Descent Nearest Neighbors Gaussian Processes Cross decomposition Naive Bayes Decision Trees Ensemble methods Multiclass and multilabel algorithms Feature selection Semi-Supervised Isotonic regression Probability calibration Neural network models

Gaussian mixture models Manifold learning Covariance estimation Novelty and Outlier Detection Neural network models Clustering (pt I) Clustering (pt II) Biclustering Decomposing signals in components Density Estimation